Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion [article]

Cole Hawkins, Zheng Zhang
2018 arXiv   pre-print
Streaming tensor factorization is a powerful tool for processing high-volume and multi-way temporal data in Internet networks, recommender systems and image/video data analysis. Existing streaming tensor factorization algorithms rely on least-squares data fitting and they do not possess a mechanism for tensor rank determination. This leaves them susceptible to outliers and vulnerable to over-fitting. This paper presents a Bayesian robust streaming tensor factorization model to identify sparse
more » ... tliers, automatically determine the underlying tensor rank and accurately fit low-rank structure. We implement our model in Matlab and compare it with existing algorithms on tensor datasets generated from dynamic MRI and Internet traffic.
arXiv:1809.02153v2 fatcat:skzisc7dejevrbrwut33p6trdu